Analyzing the I/O Scalability of a Parallel Particle-in-Cell Code

Understanding the I/O behavior of parallel applications is fundamental both to optimize and propose tuning strategies for improving the I/O performance. In this paper we present the outcome of an I/O optimization project carried out for the parallel astrophysical Plasma Physics application Acronym, a well-tested particle-in-cell code for astrophysical simulations. Acronym is used on several different supercomputers in combination with the HDF5 library, providing the output in form of self-describing files. To address the project, we did a characterization of the main parallel I/O sub-system operated at LRZ. Afterwards we have applied two different strategies that improve the initial performance, providing a solution with scalable I/O. The results obtained show that the total application time is 4.5x faster than the original version for the best case.